Abstract

Chemometrics, and multivariate data analysis in particular, has become a significant component of Analytical Chemistry. This is because of the need to have mathematical methods capable of extracting the pertinent information from the ever-increasing amounts of data generated by modern instruments. Usually, these multivariate data analysis methods are concerned with the exploratory analysis of a single data matrix, as in PCA, or with relating one explanatory matrix to another descriptive matrix, as in regression methods such as PCR and PLS, or discriminant methods, such as FDA and PLS-DA.

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